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NASA NTRS2018

Bridging the Engineering and Medicine Gap

A primary challenge NASA faces is communication between the disparate entities of engineers and human system experts in life sciences. Clear communication is critical for exploration mission success from the perspective of both risk analysis and data handling. The engineering community uses probabilistic risk assessment (PRA) models to inform their own risk analysis and has extensive experience managing mission data, but does not always fully consider human systems integration (HSI). The medical community, as a part of HSI, has been working 1) to develop a suite of tools to express medical risk in quantitative terms that are relatable to the engineering approaches commonly in use, and 2) to manage and integrate HSI data with engineering data. This talk will review the development of the Integrated Medical Model as an early attempt to bridge the communication gap between the medical and engineering communities in the language of PRA. This will also address data communication between the two entities in the context of data management considerations of the Medical Data Architecture. Lessons learned from these processes will help identify important elements to consider in future communication and integration of these two groups.

Walton, M.↗
NASA NTRS2018

Unmanned Aircraft Systems Traffic Management (UTM)

UTM is an 'air traffic management' ecosystem for uncontrolled operations. UTM utilizes industry's ability to supply services under FAA's regulatory authority where these services do not exist. UTM development will ultimately enable the management of large scale, low-altitude UAS operations. Operational concept will address beyond visual line of sight UAS operations under 400 ft. AGL. Information architecture, data exchange protocols, software functions. Roles/responsibilities of FAA and operators. Performance requirements.

UTM↗
NASA NTRS2018

A Survey of Methods for Computing Best Estimates of Endoatmospheric and Exoatmospheric Trajectories

Beginning with the mathematical prediction of planetary orbits in the early seventeenth century up through the most recent developments in sensor fusion methods, many techniques have emerged that can be employed on the problem of endo and exoatmospheric trajectory estimation. Although early methods were ad hoc, the twentieth century saw the emergence of many systematic approaches to estimation theory that produced a wealth of useful techniques. The broad genesis of estimation theory has resulted in an equally broad array of mathematical principles, methods and vocabulary. Among the fundamental ideas and methods that are briefly touched on are batch and sequential processing, smoothing, estimation, and prediction, sensor fusion, sensor fusion architectures, data association, Bayesian and non Bayesian filtering, the family of Kalman filters, models of the dynamics of the phases of a rocket's flight, and asynchronous, delayed, and asequent data. Along the way, a few trajectory estimation issues are addressed and much of the vocabulary is defined.

Bernard, William P.↗
NASA NTRSDate not supplied

NASA’s Advance Information Systems Technology (AIST) Program

NASA’s Earth Science Technology Office (ESTO) develops early-stage technologies to enhance scientific understanding. ESTO’s technologies can be reliably and confidently applied to a broad range of science measurements and missions, as well as facilitate practical applications to benefit society at large. As the lead technology office within the Earth Science Division of the NASA Science Mission Directorate, ESTO is focused on the technological challenges inherent to space-based investigations of our planet's dynamic, interrelated systems. Through flexible, science-driven technology strategies and a competitive selection process, ESTO-funded technologies have supported numerous Earth science missions as well as commercial applications. From next generation sensors and instruments to communication and information systems, ESTO technologies enable many NASA missions and data services. The Advanced Information Systems Technology (AIST) Program is one focal area of ESTO. AIST innovates information system technologies that enable the development of new observing systems as well as agile science investigations through data analytics and artificial intelligence tools and algorithms. AIST utilizes an end-to-end development approach with the goal of infusing mature technologies into future missions, measurements, and analysis. One thrust of AIST is data exploitation and analysis using an analytic center framework to make observational data and model output more accessible and usable to scientists conducting specific investigations as well as to extract higher-level science content and information from the data. The framework accelerates scientific discovery by harmonizing the data, tools, and computational resources. NASA’s upcoming Surface, Biology and Geology (SBG) mission is one such mission whose data architecture will leverage many of the technologies developed through the AIST program. This talk will highlight current and future program development goals.

Laura Rogers↗
NASA NTRS2023

Automated Medical Inventory System (AMIS) TechPort Entry

The current medical inventory paradigm on the International Space Station (ISS) requires crew to report use of medications and supplies to be manually decremented by ground teams. This method is not only tedious and time consuming for both the crew and ground teams but also results in inaccuracies in location and availability of medical supplies over time. Fortunately, the ISS is frequently resupplied by cargo launches and crew expeditions, and an accurate inventory count is less critical. However, for exploration missions, resupply will be greatly limited or unavailable entirely, and increasing communication latency will impair crew-ground communications. On longer missions, with large medical systems and time constrained crew, NASA needs a method of accurately managing medical inventory without reliance on ground teams and with as little crew time and effort as possible. The Exploration Medical Integrated Product Team (XMIPT) project called Medical Exploration Development and Implementation Scoping (MEDIScope) prepared a concept of operations and preliminary requirements for an Automated Medical Inventory System (AMIS) and completed a market survey and trade study of potential inventory management technologies in partnership with the market research firm, yet2. The products from the MEDIScope effort, including the market survey results, preliminary functional requirements and a concept of operations, have been handed off to a development team at Glenn Research Center (GRC) and ZIN Technologies for technology maturation. In the development phase, the AMIS team will finalize system requirements, down select technologies, integrate with a future exploration Crew Health and Performance Integrated Data Architecture, and conduct design reviews. The project will culminate in an ISS technical flight demonstration in FY27.

MEDIScope↗
NASA NTRSDate not supplied

Earth-Independent Medical Operations (EIMO) Concept of Operations

Compared to the current paradigm for crew health in low-Earth orbit and Lunar missions that rely on constant communication with Mission Control, there is an anticipated shift in medical operations for deep-space exploration missions. This shift stems from mission constraints imposed by the considerable distance from Earth, which include resource limitations due to a lack of resupply, mass, power, volume, and data limitations, challenges imposed by communication latency and the inability to evacuate in case of emergencies. To transition towards a more self-reliant medical approach, a comprehensive strategy is essential to progressively enable crew autonomy and mitigate mission success risks in the challenging environment of space. This transformative shift is collectively referred to as "Earth-Independent Medical Operations" (EIMO), signifying the gradual transfer of medical care and decision-making from terrestrial resources to space-based assets. This transition is aimed at bolstering astronaut health and performance while simultaneously reducing the overall risks associated with space missions. The constraints related to EIMO necessitate an integrated development of medical systems, featuring interoperability with mission planning, vehicle design, spacesuit design, and data architecture. This integration is vital in establishing a robust medical infrastructure that not only supports the well-being of astronauts but also ensures the success of the mission as a whole. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has developed a model-based Concept of Operations (ConOps) outlining an initial vision for EIMO. Within this ConOps, a comprehensive view is presented, encompassing stakeholder needs, system objectives, and system goals associated with EIMO. Additionally, it provides illustrative examples of the various activities (scenarios) for which the system will be employed during missions. The selection of these activities has been meticulous, aiming to encompass a wide spectrum of medical conditions, including those falling under different risk categories, such as low-likelihood-low-consequence, low-likelihood-high-consequence, and high-likelihood-low-consequence. The selection of these activities (scenarios) effectively encompasses the wide range of medical events situated within an assumed probability-consequence bell curve. In each scenario, at least one of the five main EIMO components identified is captured. Those EIMO components are: Pre-mission Planning, Acute and Emergent Management Decision Making, Prolonged Medical Management Decision Making, Supplies and Resource Management, and Task Load Management. The ConOps was developed by a multidisciplinary team consisting of systems engineers, scientists, and clinicians across NASA and aims to serve as an initial recommendation to gradually and safely enabling crew autonomy for Mars missions and beyond.

Earth Independent Medical Operations↗
NASA NTRS2023

Progressively Enabling Earth Independent Medical Operations (EIMO)

This panel presents the findings from a series of Technical Interchange Meetings (TIMs) hosted by the Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program. The topics for the TIMs were derived from a 2-day conference of senior leaders and subject matters experts that collectively outlined a multi-faceted strategy designed to optimize crew health and performance through an increasingly autonomous medical approach. The first abstract in this panel outlines the scope of issues related to data collection, usage, transmission and computing capacity to facilitate EIMO. The second presentation provides an overview of the challenges in developing curricula and advanced training tools to baseline knowledge, skills and abilities (KSA), verify clinical competency and assure retention during prolonged durations inherent in exploration-class missions. An overview of the complicated medical supply and resource chain necessary to facilitate EIMO is provided in the third presentation of this panel. The final presentation in this EIMO panel surveys the breadth and depth of demands on cognitive load expected to be experienced by crew on an exploration mission and proposes strategies to mitigate the prospect of cognitive overload through methods to shift task load from the crew to multi-modal artificial intelligence based medical support systems. Taken together, these presentations summarize the challenges to be expected and potential solution spaces to be explored and developed to progressively enable increasing autonomous medical operations to support crewed missions beyond low earth orbit. Through EIMO focused pre-mission planning, integrated data architecture design, innovative training development and AI-assisted task load management, the gradual transition of medical care and decision making from terrestrial to space-based assets enabling support of astronaut health and performance and reducing overall mission risk is achievable.

Jay Lemery↗
NASA NTRSDate not supplied

Progressively Enabling Earth Independent Medical Operations (EIMO)

This panel presents the findings from a series of Technical Interchange Meetings (TIMs) hosted by the Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program. The topics for the TIMs were derived from a 2-day conference of senior leaders and subject matters experts that collectively outlined a multi-faceted strategy designed to optimize crew health and performance through an increasingly autonomous medical approach. The first abstract in this panel outlines the scope of issues related to data collection, usage, transmission and computing capacity to facilitate EIMO. The second presentation provides an overview of the challenges in developing curricula and advanced training tools to baseline knowledge, skills and abilities (KSA), verify clinical competency and assure retention during prolonged durations inherent in exploration-class missions. An overview of the complicated medical supply and resource chain necessary to facilitate EIMO is provided in the third presentation of this panel. The final presentation in this EIMO panel surveys the breadth and depth of demands on cognitive load expected to be experienced by crew on an exploration mission and proposes strategies to mitigate the prospect of cognitive overload through methods to shift task load from the crew to multi-modal artificial intelligence based medical support systems. Taken together, these presentations summarize the challenges to be expected and potential solution spaces to be explored and developed to progressively enable increasing autonomous medical operations to support crewed missions beyond low earth orbit. Through EIMO focused pre-mission planning, integrated data architecture design, innovative training development and AI-assisted task load management, the gradual transition of medical care and decision making from terrestrial to space-based assets enabling support of astronaut health and performance and reducing overall mission risk is achievable.

John Lemery↗
NASA NTRSDate not supplied

Exploration Medical Capability - Advancing Medical System Design and Risk-Informed Decision Making for Deep Space Exploration

BACKGROUND: Within NASA’s Human Research Program, the Exploration Medical Capability (ExMC) Element has three primary focus areas: clinical and scientific research, systems engineering and trade space analysis, and technology development and demonstrations. These focus areas feed into the overarching goal of enabling progressively Earth-Independent Medical Operations (EIMO), a new paradigm that will be necessary for future Artemis and Mars medical and vehicle systems. This EIMO end state aligns with NASA’s Moon to Mars Objectives, which clearly outline the need for NASA deep space exploration missions to reduce their reliance upon Earth and become increasingly autonomous, in preparation for the first human Mars mission. OVERVIEW: To advance exploration medical systems and ultimately, integrated crew health and performance systems, ExMC’s portfolio includes: funding ground development & testing of novel medical capabilities; creation of new approaches for the development of medical protocols and procedures; deployment of innovative technologies into analog environments; technology demonstrations in spaceflight; and eventual transition to operations of new capabilities for deep space exploration missions. The portfolio also includes: pharmaceutical research targeting stability, pharmacokinetics, and pharmacodynamics; integrated data architectures and clinical decision support tools; and systems engineering and trade space analysis tools to assist NASA in the development of future medical system models as well as the medical system requirements that can serve as a foundation for deep space exploration missions. All of these investments are done in a collaborative and coordinated fashion with other NASA stakeholders, such as the Environmental Control and Life Support Systems – Crew Health and Performance System Capability Leadership Team and the Health and Medical Technical Authority. DISCUSSION: In this presentation, ExMC will provide an overview of our work from across our portfolio, all of which will inform future EIMO efforts at NASA. ExMC’s research and development investments are targeted to reduce the human system risks associated with deep space exploration to the Moon and Mars.

Kris Lehnhardt↗
NASA NTRS2024

Earth-Independent Medical Operations (EIMO) Concept of Operations (ConOps)

Compared to the current paradigm for crew health in low-Earth orbit and Lunar missions that rely on constant communication with Mission Control, there is an anticipated shift in medical operations for deep-space exploration missions. This shift stems from mission constraints imposed by the considerable distance from Earth, which include resource limitations due to a lack of resupply, mass, power, volume, and data limitations, challenges imposed by communication latency and the inability to evacuate in case of emergencies. To transition towards a more self-reliant medical approach, a comprehensive strategy is essential to progressively enable crew autonomy and mitigate mission success risks in the challenging environment of space. This transformative shift is collectively referred to as "Earth-Independent Medical Operations" (EIMO), signifying the gradual transfer of medical care and decision-making from terrestrial resources to space-based assets. This transition is aimed at bolstering astronaut health and performance while simultaneously reducing the overall risks associated with space missions. The constraints related to EIMO necessitate an integrated development of medical systems, featuring interoperability with mission planning, vehicle design, spacesuit design, and data architecture. This integration is vital in establishing a robust medical infrastructure that not only supports the well-being of astronauts but also ensures the success of the mission as a whole. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has developed a model-based Concept of Operations (ConOps) outlining an initial vision for EIMO. Within this ConOps, a comprehensive view is presented, encompassing stakeholder needs, system objectives, and system goals associated with EIMO. Additionally, it provides illustrative examples of the various activities (scenarios) for which the system will be employed during missions. The selection of these activities has been meticulous, aiming to encompass a wide spectrum of medical conditions, including those falling under different risk categories, such as low-likelihood-low-consequence, low-likelihood-high-consequence, and high-likelihood-low-consequence. The selection of these activities (scenarios) effectively encompasses the wide range of medical events situated within an assumed probability-consequence bell curve. In each scenario, at least one of the five main EIMO components identified is captured. Those EIMO components are: Pre-mission Planning, Acute and Emergent Management Decision Making, Prolonged Medical Management Decision Making, Supplies and Resource Management, and Task Load Management. The ConOps was developed by a multidisciplinary team consisting of systems engineers, scientists, and clinicians across NASA and aims to serve as an initial recommendation to gradually and safely enabling crew autonomy for Mars missions and beyond.

Earth Independent Medical Operations↗
NASA NTRSDate not supplied

A Multi-Faceted Approach to Demonstrating Multi-Functional Integrated Medical Devices to Advance Earth-Independent Medical Operations

INTRODUCTION TO MIM DEVICES Multi-functional Integrated Medical (MIM) devices conveniently incorporate multiple medical system capabilities within one device. The NASA Exploration Medical Integrated Product Team (XM-IPT) sponsored a market survey and trade study which identified the Tempus ProTM and the LifeBot 10® as the MIM devices that best met the evaluation criteria of the trade study. The Tempus ProTM (Remote Diagnostic Technologies, Ltd., Philips Corp., Farnborough, UK) and LifeBot 10® (LifeBot Health, Chicago, IL) both provide vital sign measurements such as blood pressure, electrocardiograms, heart rate, end tidal CO2, respiration rate, pulse oximetry and temperature along with ultrasound imaging. A video laryngoscopy capability is unique to the Tempus ProTM, while the LifeBot 10® supports connectivity with a digital stethoscope, otoscope, eye exam camera, and dermatoscope. Both devices include procedural guidance capabilities and have various data transmission and report generation features. TECHNOLOGY DEMONSTRATIONS NASA’s exploration-class missions will have severe resource constraints, long return trip durations, significant communication delays, and limited resupply opportunities. The medical systems of these missions will need to fit within an Earth-Independent Medical Operations (EIMO) construct. Key features of an EIMO medical system include: 1) technologies that support the prevention, diagnosis, and treatment of spaceflight medical events; 2) components that meet mass, volume, power and crew time/training constraints; 3) consideration of the medical skill level of the astronaut caregiver; 4) collection, storage and analysis of medical data within a central data architecture; and 5) incorporation of appropriate guidance and support tools that allow crew autonomy. Evaluations are underway to determine if it will be beneficial to include MIM devices within exploration medical systems by conducting a series of planned technical demonstrations. Exploration Atmosphere Chamber studies are being performed to determine MIM functionality in a high oxygen concentration atmosphere. A side-by-side comparison of the Tempus ProTM and LifeBot 10® will be performed during ground-based demonstrations. Use of the MIM devices within an EIMO medical scenario simulation will be practiced during ground-based demonstrations in preparation for International Space Station (ISS) demonstrations of the MIM device. These various demonstrations are designed to gather evidence for or against the inclusion of MIM devices within an EIMO medical system. EXPECTED DEMONSTRATION OUTCOMES Information will be gained about the feasibility, benefits, and challenges of using a multifunctional, all-in-one, medical device for medical diagnosis. Information will also be collected about performance differences as available ground support decreases. Gaining this understanding will allow for further development of exploration medical system capabilities, which take the EIMO construct into consideration.

B. E. Lewandowski↗
NASA NTRS2025

Evaluating the Viability of Compact and Portable X-Ray Systems for an Exploration Medical System in a Ground Demonstration

MOTIVATION FOR INCLUDING X-RAY CAPABILITIES For upcoming exploration missions, the need for enhanced medical care becomes critical due to extended mission durations, significant communication delays, and minimal evacuation opportunities. Previous evidence by our team has revealed that among the 119 medical conditions targeted for management during spaceflight within NASA Exploration Medical Capability’s IMPACT Condition List, at least 36 could benefit from radiography (XR). Utilizing XR for diagnosis and management is hypothesized to significantly improve management of crew health by enabling the immediate evaluation and confirmation of potential injuries or illnesses. Beyond clinical applications, XR also holds potential for non-destructive testing (NDT). This includes applications such as assessing the structural integrity of the spacecraft, analyzing surface and meteorite samples, and inspecting onboard electronics. THREE CANDIDATE X-RAY SYSTEMS CHOSEN FOR GROUND DEMONSTRATION The Exploration Medical Capability Element (ExMC) and the Exploration Medical Integrated Product Team (XMIPT) of the Mars Campaign Office initiated early background work for ground demonstrations. In FY21, ExMC published a Concept of Operations to guide requirements development. By FY23, XMIPT and yet2, a technology scouting and open innovation consulting firm, had completed a market survey and trade study to identify potential miniature XR systems. Selection criteria included commercial-off-the-shelf availability, low mass and volume, and regulatory compliance. The top three candidate devices—Remedi REMEX-KA6, MinXray Impact, and FujiFilm Xair—were acquired to characterize the requirements and capabilities of each device. To facilitate testing, phantoms, and radiographic personal protective equipment (PPE) were purchased, and a dedicated space was designated for XRS usage at Glenn Research Center. During this presentation, the mass, volume, and power requirements for each of the three piloted devices are revealed, as well as information regarding the detector, mA, and kV of the devices. GOAL AND OBJECTIVES OF A MINI XRS GROUND DEMONSTRATION The primary goal of ExMC/XMIPT technology demonstrations is to bridge the gap in available, flight-ready medical device technology by flight-testing diagnostic and treatment technologies essential for managing medical conditions during exploration missions. These technologies must adhere to vehicle constraints such as mass, volume, power, and data requirements, integrate seamlessly with medical decision-support tools, and support increasingly Earth-independent operations. There are three main objectives for the future ground demonstration of these three devices. First, we aim to determine the full capabilities of these three miniature XR systems within the context of the spaceflight environment. While medical applications are the primary focus for the miniature XR, a comprehensive exploration of non-medical uses has been initiated by an XMIPT-sponsored NASA SPARK campaign to identify collaborators. Second, we plan to establish criteria and to use insights gained from evaluating each miniature XR against those criteria to select the most suitable system among the three candidates. Third, we intend to evaluate their suitability for flight certification, which includes assessing its durability for launch, reentry, and exposure to high background radiation, as well as its compatibility with existing data architecture systems. Numerous subject matter experts from NASA and partner institutions will support these objectives.

C A Haddix↗
NASA NTRSDate not supplied

DRF: A Software Architecture for a Data Marketplace to Support Advanced Air Mobility

Advanced Air Mobility is a new aviation vision, where unmanned aerial systems will trans- port passengers and cargo across urban and rural areas. Critical to the realization of this vision is the development of a digital marketplace, which allows service providers and consumers operating in the airspace ecosystem to securely exchange data and reasoning insights. In this paper, we present the architecture of a decentralized data marketplace that connects data and reasoning service providers to vehicles and other service consumers along the cloud-to-edge continuum. We also present two example use cases to demonstrate the value of our approach.

Autonomy↗
NASA NTRS2012

Data Acquisition System Architecture and Capabilities At NASA GRC Plum Brook Station's Space Environment Test Facilities

Very large space environment test facilities present unique engineering challenges in the design of facility data systems. Data systems of this scale must be versatile enough to meet the wide range of data acquisition and measurement requirements from a diverse set of customers and test programs, but also must minimize design changes to maintain reliability and serviceability. This paper presents an overview of the common architecture and capabilities of the facility data acquisition systems available at two of the world?s largest space environment test facilities located at the NASA Glenn Research Center?s Plum Brook Station in Sandusky, Ohio; namely, the Space Propulsion Research Facility (commonly known as the B-2 facility) and the Space Power Facility (SPF). The common architecture of the data systems is presented along with details on system scalability and efficient measurement systems analysis and verification. The architecture highlights a modular design, which utilizes fully-remotely managed components, enabling the data systems to be highly configurable and support multiple test locations with a wide-range of measurement types and very large system channel counts.

Evans, Richard K.↗
NASA NTRS2014

Data Acquisition System Architecture and Capabilities at NASA GRC Plum Brook Station's Space Environment Test Facilities

Very large space environment test facilities present unique engineering challenges in the design of facility data systems. Data systems of this scale must be versatile enough to meet the wide range of data acquisition and measurement requirements from a diverse set of customers and test programs, but also must minimize design changes to maintain reliability and serviceability. This paper presents an overview of the common architecture and capabilities of the facility data acquisition systems available at two of the world's largest space environment test facilities located at the NASA Glenn Research Center's Plum Brook Station in Sandusky, Ohio; namely, the Space Propulsion Research Facility (commonly known as the B-2 facility) and the Space Power Facility (SPF). The common architecture of the data systems is presented along with details on system scalability and efficient measurement systems analysis and verification. The architecture highlights a modular design, which utilizes fully-remotely managed components, enabling the data systems to be highly configurable and support multiple test locations with a wide-range of measurement types and very large system channel counts.

Evans, Richard K.↗
NASA NTRS1999

3-D VLSI Architecture Implementation for Data Fusion Problems

This paper gives an overview of hardware implementation techniques employed in solving real-time classification problems using Neural Network, Principle Component Analysis (PCA), and Independent Component Analysis (ICA) techniques.

3-D VLSI architecture data fusion neural networks↗
NASA NTRS2000

Automatic Data Traffic Control on DSM Architecture

We study data traffic on distributed shared memory machines and conclude that data placement and grouping improve performance of scientific codes. We present several methods which user can employ to improve data traffic in his code. We report on implementation of a tool which detects the code fragments causing data congestions and advises user on improvements of data routing in these fragments. The capabilities of the tool include deduction of data alignment and affinity from the source code; detection of the code constructs having abnormally high cache or TLB misses; generation of data placement constructs. We demonstrate the capabilities of the tool on experiments with NAS parallel benchmarks and with a simple computational fluid dynamics application ARC3D.

Frumkin, Michael↗